| Type | VIDs | Transits | mean | sd | max | mean | sd | min | max | mean | sd | min | max | mean | sd | min | max |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cargo ship | 54 | 157 | 12.7 | 1.7 | 17.1 | 159 | 53 | 26 | 200 | 26 | 8 | 7 | 33 | 8.2 | 2.6 | 3.0 | 11.0 |
| Cargo ship:DG,HS,MP(X) | 1 | 2 | 11.9 | 0.7 | 13.7 | 67 | 0 | 67 | 67 | 13 | 0 | 13 | 13 | 5.0 | 0.0 | 5.0 | 5.0 |
| Diving op. | 1 | 4 | 7.8 | 0.7 | 10.0 | 10 | 0 | 10 | 10 | 4 | 0 | 4 | 4 | 0.5 | 0.0 | 0.5 | 0.5 |
| Dredging or underwater op. | 3 | 36 | 9.7 | 2.4 | 15.0 | 63 | 34 | 35 | 119 | 14 | 6 | 9 | 22 | 4.4 | 0.5 | 4.0 | 5.0 |
| Fishing | 308 | 829 | 8.4 | 3.2 | 32.2 | 20 | 9 | 6 | 100 | 6 | 2 | 1 | 20 | 1.5 | 1.2 | 0.4 | 10.0 |
| HSC | 3 | 8 | 13.0 | 8.1 | 28.6 | 25 | 13 | 7 | 35 | 7 | 3 | 3 | 10 | 2.6 | 1.7 | 0.4 | 4.0 |
| Law enforcement | 3 | 3 | 9.7 | 1.5 | 12.6 | 42 | 16 | 26 | 68 | 8 | 3 | 6 | 14 | 2.8 | 0.8 | 2.0 | 4.0 |
| Local ship | 2 | 10 | 12.4 | 6.5 | 26.5 | 13 | 4 | 10 | 18 | 4 | 0 | 4 | 5 | 0.6 | 0.2 | 0.5 | 0.9 |
| Military op. | 1 | 4 | 9.1 | 2.4 | 15.0 | 33 | 0 | 33 | 33 | 8 | 0 | 8 | 8 | 3.0 | 0.0 | 3.0 | 3.0 |
| Other | 22 | 78 | 8.6 | 2.4 | 24.9 | 37 | 22 | 6 | 76 | 9 | 5 | 2 | 20 | 3.3 | 1.9 | 0.3 | 6.0 |
| Passenger ship | 58 | 803 | 15.1 | 5.7 | 35.6 | 108 | 75 | 11 | 301 | 18 | 10 | 3 | 36 | 4.0 | 2.2 | 0.6 | 8.0 |
| Passenger ship:DG,HS,MP(Y) | 1 | 2 | 11.1 | 0.4 | 11.8 | 64 | 0 | 64 | 64 | 12 | 0 | 12 | 12 | 3.0 | 0.0 | 3.0 | 3.0 |
| Pilot | 2 | 6 | 19.9 | 3.1 | 25.8 | 19 | 1 | 17 | 20 | 4 | 1 | 3 | 5 | 1.0 | 0.0 | 1.0 | 1.0 |
| Pleasure Craft | 275 | 1213 | 8.2 | 3.7 | 37.5 | 20 | 16 | 7 | 154 | 6 | 3 | 1 | 18 | 1.1 | 1.0 | 0.4 | 9.0 |
| Port tender | 1 | 2 | 7.4 | 1.1 | 8.8 | 26 | 0 | 26 | 26 | 8 | 0 | 8 | 8 | 8.0 | 0.0 | 8.0 | 8.0 |
| Sailing | 117 | 426 | 6.0 | 1.3 | 12.6 | 14 | 4 | 8 | 35 | 4 | 1 | 1 | 8 | 0.7 | 0.3 | 0.4 | 3.0 |
| Search/rescue | 14 | 193 | 10.3 | 4.0 | 39.2 | 52 | 15 | 7 | 83 | 11 | 3 | 2 | 17 | 4.6 | 1.0 | 0.4 | 6.0 |
| Tanker | 2 | 7 | 12.1 | 0.8 | 13.9 | 141 | 5 | 134 | 145 | 24 | 0 | 24 | 24 | 8.7 | 0.5 | 8.0 | 9.0 |
| Towing | 36 | 356 | 7.0 | 1.7 | 21.7 | 27 | 21 | 6 | 162 | 8 | 3 | 4 | 24 | 3.3 | 1.8 | 0.3 | 7.0 |
| Towing(200/25) | 42 | 382 | 8.8 | 1.6 | 13.7 | 32 | 6 | 12 | 41 | 10 | 2 | 2 | 12 | 4.7 | 1.4 | 1.7 | 7.0 |
| Tug | 62 | 873 | 7.4 | 1.8 | 13.9 | 27 | 28 | 11 | 178 | 8 | 3 | 4 | 22 | 3.1 | 1.8 | 0.6 | 6.0 |
| Vessel type | IDs | Transits | Transits/day | mean | sd | max | mean | sd | min | max | mean | sd | min | max | mean | sd | min | max |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cargo > 180m | 4 | 4 | 0.01 | 12.4 | 1.6 | 14.6 | 187 | 8 | 180 | 200 | 31 | 1 | 30 | 32 | 10.2 | 0.9 | 9.0 | 11 |
| Fishing < 60m | 30 | 75 | 0.21 | 8.2 | 4.3 | 32.2 | 17 | 6 | 10 | 37 | 6 | 2 | 4 | 12 | 1.2 | 0.9 | 0.5 | 6 |
| Other < 40m | 6 | 20 | 0.05 | 8.8 | 4.9 | 31.5 | 26 | 8 | 7 | 40 | 6 | 2 | 2 | 9 | 2.0 | 1.7 | 0.4 | 5 |
| Other > 100m | 5 | 9 | 0.02 | 10.4 | 2.0 | 13.5 | 157 | 19 | 134 | 178 | 18 | 8 | 4 | 29 | 6.6 | 1.6 | 4.0 | 9 |
| Other > 40m | 13 | 59 | 0.16 | 9.5 | 2.4 | 15.0 | 55 | 14 | 42 | 98 | 13 | 3 | 9 | 22 | 3.9 | 1.4 | 2.0 | 6 |
| Passenger > 180m | 5 | 19 | 0.05 | 18.1 | 2.5 | 22.0 | 270 | 39 | 197 | 301 | 33 | 1 | 28 | 34 | 7.8 | 0.4 | 7.0 | 8 |
| Pleasurecraft < 40m | 70 | 142 | 0.39 | 7.4 | 3.6 | 34.4 | 15 | 5 | 7 | 28 | 5 | 1 | 2 | 7 | 0.7 | 0.2 | 0.4 | 2 |
| Sailing | 17 | 35 | 0.10 | 5.6 | 1.4 | 9.0 | 15 | 5 | 8 | 32 | 4 | 2 | 2 | 8 | 0.8 | 0.4 | 0.4 | 3 |
| Towing < 50m | 14 | 40 | 0.11 | 9.2 | 1.4 | 11.8 | 34 | 4 | 26 | 41 | 10 | 2 | 6 | 12 | 5.2 | 1.2 | 1.7 | 6 |
| Tug < 50m | 17 | 74 | 0.20 | 7.1 | 1.9 | 11.2 | 23 | 9 | 12 | 41 | 8 | 2 | 4 | 12 | 3.2 | 1.7 | 0.6 | 6 |
Figure S1. Length distributions of the ten vessel classes used to summarize marine traffic in 2019.
Figure S2. Speed distributions, in knots, of the ten vessel classes used to summarize marine traffic in 2019.
Figure S3. Seasonal patterns in the speed (knots) of marine traffic, grouped iinto the 10 vessel classes used in this study.
Figure S4.Seasonal patterns in the length (meters) of marine traffic, grouped iinto the 10 vessel classes used in this study.
| Vessel class | 2014 | 2015 | 2018 | 2019 | 2030 | Scale factor | 2019 | 2039 | p-value |
|---|---|---|---|---|---|---|---|---|---|
| Cargo > 180m | 0 | 0 | 0 | 9444 | 16943 | 1.79 | 0.15 | 0.08 | 0.30 |
| Fishing < 60m | 17165 | 16377 | 31949 | 45784 | 86437 | 1.89 | 0.12 | 0.06 | 0.05 |
| Other < 40m | 62201 | 87269 | 57399 | 18723 | 0 | 0.00 | -0.48 | -0.24 | 0.24 |
| Other > 100m | 25213 | 19011 | 27281 | 26166 | 33552 | 1.28 | 0.03 | 0.03 | 0.44 |
| Other > 40m | 27391 | 9943 | 23408 | 29184 | 37725 | 1.29 | 0.05 | 0.04 | 0.60 |
| Passenger > 180m | 6212 | 5489 | 10403 | 6168 | 11554 | 1.87 | 0.07 | 0.04 | 0.55 |
| Pleasurecraft < 40m | 0 | 0 | 56 | 51215 | 91952 | 1.80 | 0.15 | 0.08 | 0.30 |
| Sailing | 357 | 1553 | 12538 | 20934 | 50795 | 2.43 | 0.19 | 0.08 | 0.02 |
| Towing < 50m | 35311 | 15299 | 39409 | 42838 | 67175 | 1.57 | 0.08 | 0.05 | 0.38 |
| Tug < 50m | 30971 | 44685 | 46344 | 43301 | 61901 | 1.43 | 0.05 | 0.03 | 0.33 |
Figure S5. Changes in total transit kilometers for the 10 vessel classes in our study, 2014 - 2019.
Table S4. Dimensions of the LNG Canada fleet, adapted from TERMPOL (2015). Note that in our analyses, we reduced the max Shell length to 298m, and the beam was adjusted according to the original length:beam ratio.
| Year | segments | km | total | valid | total | valid |
|---|---|---|---|---|---|---|
| 2013 | 143 | 712.5204 | 8 | 6 | 68 | 38 |
| 2014 | 168 | 800.5337 | 18 | 17 | 134 | 130 |
| 2015 | 402 | 2083.1364 | 19 | 19 | 253 | 251 |
Figure S6. (a) Design-based line-transect survey effort throughout the central Gitga’at waters of the Kitimat Fjord System (each dot is the center of a 5-km segment of systematic effort), yielding detections of (b) fin whales and (c) humpback whales. Detection dot size reflects group size
| Species | Model | Key function | Formula | C-vM p-value | \(\hat{P_a}\) | se(\(\hat{P_a}\)) | \(\Delta\)AIC | |
|---|---|---|---|---|---|---|---|---|
| 1 | Fin whale | 1 | Half-normal | ~1 | 0.8405095 | 0.5500191 | 0.0742873 | 0.0000000 |
| 3 | 2 | Half-normal | ~1 + factor(year) | 0.7815848 | 0.5231299 | 0.0742940 | 0.3047398 | |
| 2 | 3 | Half-normal | ~1 + bft | 0.8250065 | 0.5465154 | 0.0793721 | 1.5958236 | |
| 31 | Humpback whale | 1 | Half-normal | ~1 + factor(year) | 0.9652267 | 0.5204825 | 0.0213641 | 0.0000000 |
| 21 | 2 | Half-normal | ~1 + bft | 0.9637787 | 0.5296131 | 0.0215150 | 9.0061244 | |
| 11 | 3 | Half-normal | ~1 | 0.9430440 | 0.5364511 | 0.0213979 | 15.9211900 |
Figure S7. Best-fitting detection function models superimposed upon histograms of detection distances for each species.
Figure S8. Bathymetric characteristics of the study area, as summarized for the square-kilometer grid used in density surface modeling.
| Whale ID | Total | Score 1 | Score 2 | Mean | SD | Score 1 | Score 2 | Mean | SD | Score 1 | Score 2 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 20190611 1A | 5 | 3 | 2 | 11.19 | 0.27 | 11.09 | 11.34 | 3.52 | 0.11 | 3.49 | 3.60 |
| 20190829 1A | 1 | 1 | 0 | 11.08 | 11.08 | 3.58 | 3.58 | ||||
| 20190829 1B | 4 | 1 | 3 | 10.92 | 0.33 | 11.10 | 10.86 | 3.76 | 0.15 | 3.92 | 3.69 |
| 20190905 1A | 10 | 4 | 6 | 11.17 | 0.62 | 11.08 | 11.22 | 3.93 | 0.22 | 3.89 | 3.96 |
| 20190905 1B | 2 | 1 | 1 | 11.39 | 0.20 | 11.25 | 11.53 | 4.21 | 0.08 | 4.27 | 4.15 |
| 20190905 2A | 4 | 2 | 2 | 14.45 | 0.29 | 14.68 | 14.22 | 4.38 | 0.11 | 4.44 | 4.33 |
| 20190905 2B | 3 | 2 | 1 | 13.26 | 0.28 | 13.42 | 12.94 | 4.21 | 0.10 | 4.17 | 4.28 |
| 20190907 1A | 3 | 1 | 2 | 11.67 | 0.22 | 11.90 | 11.55 | 3.98 | 0.03 | 3.96 | 3.99 |
| 20190908 1A | 1 | 1 | 0 | 10.97 | 10.97 | 3.53 | 3.53 | ||||
| 20190909 1A | 3 | 2 | 1 | 13.34 | 0.11 | 13.34 | 13.32 | 4.44 | 0.12 | 4.51 | 4.30 |
| 20190909 1B | 5 | 2 | 3 | 10.41 | 0.35 | 10.77 | 10.17 | 3.59 | 0.10 | 3.67 | 3.53 |
| 20190910 1A | 1 | 0 | 1 | 12.36 | 12.36 | 4.01 | 4.01 | ||||
| 20190911 1A | 8 | 3 | 5 | 10.94 | 0.48 | 10.93 | 10.95 | 3.54 | 0.10 | 3.54 | 3.54 |
| 20190911 1B | 1 | 0 | 1 | 11.08 | 11.08 | 3.96 | 3.96 | ||||
| 20191004 1A | 9 | 7 | 2 | 13.64 | 0.21 | 13.68 | 13.49 | 4.13 | 0.06 | 4.13 | 4.09 |
| Date | File | Follows | Mean | Total | Mean | Total | Speed (m/s) |
|---|---|---|---|---|---|---|---|
| 2019-06-06 | 20190606_DJI_0079 | 1 | 31.00 | 31 | 0.03 | 0.03 | 0.836 |
| 2019-08-28 | 20190828_DJI_0552_Group1 | 1 | 43.00 | 43 | 0.00 | 0.00 | 0.039 |
| 2019-08-29 | 20190829_DJI_0556_Group1 | 3 | 50.67 | 152 | 0.03 | 0.08 | 0.501 |
| 2019-09-03 | 20190903_DJI_0564_Group1 | 1 | 68.00 | 68 | 0.07 | 0.07 | 1.017 |
| 2019-09-05 | 20190905_DJI_0575_Group1 | 1 | 71.00 | 71 | 0.01 | 0.01 | 0.210 |
| 2019-09-05 | 20190905_DJI_0578_Group1 | 2 | 84.50 | 169 | 0.04 | 0.07 | 0.430 |
| 2019-09-05 | 20190905_DJI_0582_Group2 | 1 | 42.00 | 42 | 0.03 | 0.03 | 0.768 |
| 2019-09-05 | 20190905_DJI_0585_Group2 | 2 | 50.50 | 101 | 0.02 | 0.04 | 0.353 |
| 2019-09-07 | 20190907_DJI_0591_Group3 | 2 | 48.00 | 96 | 0.03 | 0.06 | 0.675 |
| 2019-09-07 | 20190907_DJI_0593_Group3 | 2 | 98.00 | 196 | 0.07 | 0.15 | 0.754 |
| 2019-09-08 | 20190908_DJI_0597_Group1and2 | 1 | 41.00 | 41 | 0.02 | 0.02 | 0.580 |
| 2019-09-08 | 20190908_DJI_0600_Group3 | 1 | 64.00 | 64 | 0.03 | 0.03 | 0.525 |
| 2019-09-11 | 20190911_DJI_0620_Group2 | 2 | 46.50 | 93 | 0.04 | 0.08 | 0.812 |
| 2019-10-04 | 20191004_DJI_0624_Group1 | 1 | 78.00 | 78 | 0.05 | 0.05 | 0.663 |
Figure S9. Raw time- and depth-distributions of depth sensor readings for each of the 7 SPLASH-10 tag deployments.
Figure S10. Time distribution (hour of day, color-coded by daytime/nighttime) of depth samples from SPLASH10 tags, displayed for each deployment separately.
| This study | Nichol et al. (2018) | Start | Stop | Hours | Hours valid | Total | Day | Night | Prop. valid |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 132219-132219 | 2013-08-19 23:00:00 | 2013-08-24 20:58:45 | 117.97917 | 8.00000 | 384 | 336 | 48 | 0.07 |
| 2 | 132220-132220 | 2013-08-18 18:47:30 | 2013-08-28 19:57:30 | 241.16667 | 26.18750 | 1257 | 837 | 420 | 0.11 |
| 3 | 137684-137684 | 2014-08-16 00:15:00 | 2014-08-16 23:57:30 | 23.70833 | 23.72917 | 1139 | 835 | 304 | 1.00 |
| 4 | 137685-137685 | 2014-08-20 18:22:30 | 2014-09-04 21:58:45 | 363.60417 | 45.62500 | 2190 | 1720 | 470 | 0.13 |
| 5 | 137686-137686 | 2014-08-23 16:30:00 | 2014-09-02 13:57:30 | 237.45833 | 18.47917 | 887 | 792 | 95 | 0.08 |
| 6 | 142546-142546 | 2014-09-08 19:00:00 | 2014-09-28 23:58:45 | 484.97917 | 82.00000 | 3936 | 2468 | 1468 | 0.17 |
| 7 | 142547-142547 | 2014-09-14 00:00:00 | 2014-09-14 10:58:45 | 10.97917 | 4.00000 | 192 | 96 | 96 | 0.36 |
Figure S11. Daytime (left) and nighttime (right) depth distribution curves, representing the proportion of time spent above a given depth, for six SPLASH-10 deployments on fin whales (colored lines).
Figure S12. Probabilities of collision (left) and mortality (right) as a function of ship speed (>180m length), adapted from Gende et al. (2011) and Kelley et al. (2020), respectively.
Fin whales – Canadian Pacific stock (Wright et al. 2022):
pbr(N = 2893, CV = 0.15) %>% cbind
## .
## PBR 16.1527
## Nmin 807.6348
## Rmax 0.08
## Fr 0.5
## Nmedian 2876.57
Fin whales – North Coast Sector (Wright et al. 2022):
pbr(N = 161, CV = 0.50) %>% cbind
## .
## PBR 1.264424
## Nmin 63.2212
## Rmax 0.08
## Fr 0.5
## Nmedian 165.0474
Fin whales – coastal (Queen Charlotte, Hecate Strait) (Nichol et al 2017):
pbr(N = 405, CV = 0.6) %>% cbind
## .
## PBR 2.843767
## Nmin 142.1884
## Rmax 0.08
## Fr 0.5
## Nmedian 411.2598
Humpback whales – Canadian Pacific stock (Wright et al. 2022):
pbr(N = 7030, CV = 0.1) %>% cbind
## .
## PBR 35.1167
## Nmin 1755.835
## Rmax 0.08
## Fr 0.5
## Nmedian 6937.317
Humpback whales – North Coast sector (Wright et al. 2022):
pbr(N = 1816, CV = 0.13) %>% cbind
## .
## PBR 10.15118
## Nmin 507.5589
## Rmax 0.08
## Fr 0.5
## Nmedian 1867.264
Figure S13. Distribution of 2019 marine traffic parsed by waterway and time of day.
Figure S14. Monthly distribution of 2019 marine traffic, parsed by time of day.
Figure S15. Transit counts for 10 vessel types in 2019, displayed for each waterway in the study area separately.
| Species | Formula | Trunc. dist. | Family | Link function | Delta AIC | Deviance explained |
|---|---|---|---|---|---|---|
| Fin whale | (Lat x Lon) + seafloor depth + seafloor range | 2.0 km | Tweedie | log | 104 | 54% |
| Humpback whale | (Lat x Lon x DOY) + seafloor depth + seafloor range + year | 2.7 km | Tweedie | log | 14 | 51% |
| Waterway | Season |
|---|---|
| Caamano | 0.022 (0-0.126) |
| Campania | 0.024 (0-0.148) |
| Estevan | 0 (0-0) |
| McKay | 0 (0-0) |
| Squally | 0.031 (0-0.169) |
| Verney | 0 (0-0) |
| Whale | 0 (0-0) |
| Wright | 0 (0-0) |
| Study area | 0.014 (0-0.118) |
| Waterway | Season | June | July | August | September |
|---|---|---|---|---|---|
| Caamano | 0.059 (0.012-0.153) | 0.119 (0.006-0.74) | 0.057 (0.006-0.113) | 0.046 (0.005-0.094) | 0.049 (0.013-0.139) |
| Campania | 0.07 (0.012-0.139) | 0.056 (0.001-0.131) | 0.063 (0.01-0.158) | 0.071 (0.007-0.186) | 0.097 (0.015-0.249) |
| Estevan | 0.037 (0.004-0.071) | 0.119 (0.006-0.153) | 0.021 (0.001-0.024) | 0.046 (0.006-0.121) | 0.047 (0.008-0.107) |
| McKay | 0.049 (0.003-0.112) | 0.007 (0.001-0.036) | 0.02 (0.001-0.04) | 0.068 (0-0.134) | 0.102 (0.017-0.313) |
| Squally | 0.11 (0.025-0.251) | 0.132 (0.021-0.429) | 0.041 (0.002-0.099) | 0.161 (0.037-0.448) | 0.102 (0.01-0.2) |
| Verney | 0.072 (0.006-0.282) | 0.006 (0-0.035) | 0.029 (0.001-0.108) | 0.085 (0.006-0.231) | 0.154 (0.004-0.786) |
| Whale | 0.113 (0.023-0.298) | 0.03 (0.003-0.111) | 0.015 (0.002-0.048) | 0.196 (0.026-0.502) | 0.165 (0.034-0.512) |
| Wright | 0.117 (0.007-0.308) | 0.033 (0-0.139) | 0.081 (0.01-0.204) | 0.164 (0.034-0.566) | 0.154 (0-0.425) |
| Study area | 0.079 (0.01-0.223) | 0.083 (0.001-0.417) | 0.046 (0.002-0.125) | 0.1 (0.007-0.359) | 0.095 (0.01-0.32) |
| Family | Formula | edf | P-value of coefficient | Deviance explained |
|---|---|---|---|---|
| Negative binomial | count ~ s(doy, k=5) + offset(log(minutes)) | 2.803 | 7e-04 | 26% |
| Vessel type | Median | Mean | SD | LCI | UCI | Median | Mean | SD | LCI | UCI | FW - HW | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cargo > 180m | 0.06 | 0.061 | 0.024 | 0.02 | 0.11 | 0.05 | 0.048 | 0.022 | 0.01 | 0.10 | 0.01 | |
| Cedar LNG tanker in-heel | 0.08 | 0.086 | 0.030 | 0.04 | 0.15 | 0.07 | 0.070 | 0.025 | 0.03 | 0.12 | 0.01 | |
| Cedar LNG tanker in-product | 0.08 | 0.086 | 0.031 | 0.03 | 0.14 | 0.07 | 0.067 | 0.025 | 0.03 | 0.12 | 0.01 | |
| Cedar LNG tug in-heel | 0.02 | 0.024 | 0.015 | 0.00 | 0.06 | 0.01 | 0.016 | 0.013 | 0.00 | 0.04 | 0.01 | |
| Cedar LNG tug in-product | 0.02 | 0.023 | 0.016 | 0.00 | 0.06 | 0.02 | 0.017 | 0.012 | 0.00 | 0.04 | 0.00 | |
| Fishing < 60m | 0.02 | 0.023 | 0.015 | 0.00 | 0.05 | 0.01 | 0.015 | 0.012 | 0.00 | 0.04 | 0.01 | |
| LNG Canada tanker in-heel | 0.09 | 0.087 | 0.026 | 0.04 | 0.14 | 0.07 | 0.071 | 0.025 | 0.03 | 0.12 | 0.02 | |
| LNG Canada tanker in-product | 0.08 | 0.085 | 0.027 | 0.04 | 0.14 | 0.07 | 0.071 | 0.025 | 0.02 | 0.12 | 0.01 | |
| LNG Canada tug in-heel | 0.02 | 0.024 | 0.014 | 0.00 | 0.06 | 0.02 | 0.016 | 0.012 | 0.00 | 0.04 | 0.00 | |
| LNG Canada tug in-product | 0.02 | 0.022 | 0.015 | 0.00 | 0.05 | 0.01 | 0.015 | 0.012 | 0.00 | 0.04 | 0.01 | |
| Other < 40m | 0.02 | 0.021 | 0.014 | 0.00 | 0.05 | 0.01 | 0.016 | 0.013 | 0.00 | 0.05 | 0.01 | |
| Other > 100m | 0.04 | 0.046 | 0.021 | 0.01 | 0.09 | 0.04 | 0.038 | 0.021 | 0.01 | 0.09 | 0.00 | |
| Other > 40m | 0.03 | 0.033 | 0.017 | 0.01 | 0.07 | 0.03 | 0.026 | 0.016 | 0.00 | 0.06 | 0.00 | |
| Passenger > 180m | 0.06 | 0.061 | 0.023 | 0.02 | 0.11 | 0.05 | 0.051 | 0.020 | 0.01 | 0.10 | 0.01 | |
| Pleasurecraft < 40m | 0.02 | 0.019 | 0.014 | 0.00 | 0.05 | 0.01 | 0.015 | 0.012 | 0.00 | 0.04 | 0.01 | |
| Sailing | 0.02 | 0.019 | 0.013 | 0.00 | 0.05 | 0.01 | 0.014 | 0.012 | 0.00 | 0.04 | 0.01 | |
| Towing < 50m | 0.02 | 0.024 | 0.015 | 0.00 | 0.05 | 0.02 | 0.020 | 0.014 | 0.00 | 0.05 | 0.00 | |
| Tug < 50m | 0.02 | 0.024 | 0.015 | 0.00 | 0.06 | 0.02 | 0.019 | 0.014 | 0.00 | 0.05 | 0.00 |
Figure S16. Distributions of close-encounter rate estimates for each vessel type (row) and each whale species (color), based upon iterative simulations. Vertical lines indicate the median of each distribution. Here summertime and wintertime distributions are pooled.
| Depth (m) | Mean | SD | Mean | SD |
|---|---|---|---|---|
| 1 | 8.7% | 4.8% | 8.3% | 7.5% |
| 2 | 14.4% | 7.2% | 18.1% | 13.1% |
| 5 | 26% | 5.2% | 41.1% | 16.1% |
| 10 | 37.1% | 7.1% | 59.2% | 15.3% |
| 15 | 47.5% | 8% | 72.1% | 17% |
| 20 | 55.4% | 6.9% | 82% | 15.6% |
| 25 | 60.9% | 6.6% | 85.3% | 16% |
| 30 | 63.3% | 6.4% | 89.5% | 12.9% |
Figure S17. Daytime (pink) and nighttime (teal) depth distribution curves for fin whale in and near the Kitimat Fjord System, representing the average proportion of time spent above a given depth across all tag deployments (n=6 in 2013 and 2014). Points on the left side of the plot represent the SD at each depth.
| Traffic scheme | Event | Mean | Median | 95% CI | 80% Conf. | Mean | Median | 95% CI | 80% Conf. |
|---|---|---|---|---|---|---|---|---|---|
| AIS 2019 | Cooccurrence | 509.21 | 509.0 | 471 - 549 | 488 | 5958.69 | 5961.0 | 5820 - 6099 | 5887.0 |
| Close encounter | 13.59 | 13.5 | 8 - 19 | 10 | 119.59 | 120.0 | 102 - 138 | 110.8 | |
| Strike-zone event | 3.06 | 3.0 | 1 - 6 | 2 | 25.56 | 25.0 | 17 - 34 | 21.0 | |
| (1.5x draft) | 3.00 | 3.0 | 0 - 6 | 2 | 25.59 | 25.0 | 18 - 34 | 21.0 | |
| AIS 2030 | Cooccurrence | 855.99 | 856.0 | 802 - 912 | 827 | 9428.00 | 9428.0 | 9222 - 9638 | 9322.8 |
| Close encounter | 22.79 | 22.5 | 16 - 31 | 19 | 184.71 | 184.0 | 164 - 209 | 173.0 | |
| Strike-zone event | 4.89 | 5.0 | 2 - 9 | 3 | 39.13 | 39.0 | 29 - 50 | 34.0 | |
| (1.5x draft) | 5.03 | 5.0 | 2 - 9 | 3 | 38.87 | 38.5 | 30 - 49 | 34.0 | |
| LNG Canada | Cooccurrence | 137.66 | 137.0 | 116 - 161 | 127 | 1710.28 | 1710.0 | 1637 - 1786 | 1670.0 |
| Close encounter | 7.20 | 7.0 | 3 - 12 | 5 | 70.41 | 70.0 | 57 - 85 | 63.0 | |
| Strike-zone event | 3.01 | 3.0 | 0 - 6 | 1 | 30.11 | 30.0 | 22 - 39 | 25.0 | |
| (1.5x draft) | 3.01 | 3.0 | 0 - 6 | 1 | 30.13 | 30.0 | 21 - 40 | 25.0 | |
| Cedar LNG | Cooccurrence | 19.40 | 19.0 | 13 - 27 | 16 | 236.57 | 237.0 | 211 - 262 | 223.0 |
| Close encounter | 1.06 | 1.0 | 0 - 3 | 0 | 9.75 | 10.0 | 5 - 15 | 7.0 | |
| Strike-zone event | 0.44 | 0.0 | 0 - 2 | 0 | 4.37 | 4.0 | 1 - 8 | 3.0 | |
| (1.5x draft) | 0.45 | 0.0 | 0 - 2 | 0 | 4.33 | 4.0 | 1 - 8 | 2.0 | |
| Total 2030 | Cooccurrence | 1013.05 | 1013.5 | 954 - 1074 | 981 | 11374.85 | 11373.0 | 11154 - 11590 | 11262.8 |
| Close encounter | 31.05 | 31.0 | 23 - 40 | 26 | 264.87 | 265.0 | 239 - 292 | 251.0 | |
| Strike-zone event | 8.34 | 8.0 | 4 - 13 | 6 | 73.61 | 73.0 | 60 - 88 | 66.0 | |
| (1.5x draft) | 8.50 | 8.0 | 4 - 14 | 6 | 73.33 | 73.0 | 59 - 87 | 66.0 |
Figure S18. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2019.
Figure S19. Distribution of whale-vessel interaction rate predictions for AIS traffic in 2030.
Figure S20. Distribution of whale-vessel interaction rate predictions for LNG Canada traffic in 2030.
Figure S21. Distribution of whale-vessel interaction rate predictions for Cedar LNG traffic in 2030.
Figure S22. Distribution of whale-vessel interaction rate predictions for all traffic in 2030 (AIS and LNG combined).
| Traffic scheme | Event | Avoidance | Mean | Median | 95% CI | 80% Conf. | Mean | Median | 95% CI | 80% Conf. |
|---|---|---|---|---|---|---|---|---|---|---|
| AIS 2019 | Collision | 0.55 | 0.48 | 0 | 0 - 2 | 0 | 2.92 | 3 | 0 - 6 | 1 |
| ~ Speed | 0.77 | 1 | 0 - 2 | 0 | 3.89 | 4 | 1 - 8 | 2 | ||
| None | 1.13 | 1 | 0 - 3 | 0 | 6.44 | 6 | 2 - 11 | 4 | ||
| Mortality | 0.55 | 0.47 | 0 | 0 - 2 | 0 | 2.73 | 3 | 0 - 6 | 1 | |
| ~ Speed | 0.74 | 1 | 0 - 2 | 0 | 3.70 | 4 | 1 - 7 | 2 | ||
| None | 1.08 | 1 | 0 - 3 | 0 | 6.06 | 6 | 2 - 10 | 4 | ||
| AIS 2030 | Collision | 0.55 | 0.86 | 1 | 0 - 3 | 0 | 5.11 | 5 | 2 - 9 | 3 |
| ~ Speed | 1.33 | 1 | 0 - 3 | 0 | 6.93 | 7 | 3 - 12 | 5 | ||
| None | 1.98 | 2 | 0 - 4 | 1 | 11.54 | 11 | 6 - 17 | 9 | ||
| Mortality | 0.55 | 0.82 | 1 | 0 - 2 | 0 | 4.78 | 5 | 2 - 9 | 3 | |
| ~ Speed | 1.29 | 1 | 0 - 3 | 0 | 6.55 | 6 | 3 - 11 | 4 | ||
| None | 1.90 | 2 | 0 - 4 | 1 | 10.80 | 11 | 6 - 17 | 8 | ||
| LNG Canada | Collision | 0.55 | 1.24 | 1 | 0 - 3 | 0 | 12.39 | 12 | 7 - 19 | 9 |
| ~ Speed | 1.18 | 1 | 0 - 3 | 0 | 11.69 | 11 | 6 - 18 | 9 | ||
| None | 2.71 | 3 | 0 - 6 | 1 | 27.46 | 27 | 19 - 37 | 23 | ||
| Mortality | 0.55 | 1.06 | 1 | 0 - 3 | 0 | 10.55 | 10 | 5 - 16 | 8 | |
| ~ Speed | 1.00 | 1 | 0 - 3 | 0 | 10.16 | 10 | 5 - 16 | 7 | ||
| None | 2.29 | 2 | 0 - 5 | 1 | 23.43 | 23 | 16 - 32 | 19 | ||
| Cedar LNG | Collision | 0.55 | 0.17 | 0 | 0 - 1 | 0 | 1.74 | 2 | 0 - 4 | 1 |
| ~ Speed | 0.17 | 0 | 0 - 1 | 0 | 1.56 | 1 | 0 - 4 | 0 | ||
| None | 0.41 | 0 | 0 - 2 | 0 | 3.92 | 4 | 1 - 8 | 2 | ||
| Mortality | 0.55 | 0.15 | 0 | 0 - 1 | 0 | 1.45 | 1 | 0 - 4 | 0 | |
| ~ Speed | 0.15 | 0 | 0 - 1 | 0 | 1.31 | 1 | 0 - 4 | 0 | ||
| None | 0.35 | 0 | 0 - 2 | 0 | 3.26 | 3 | 1 - 6 | 2 | ||
| Total 2030 | Collision | 0.55 | 2.27 | 2 | 0 - 5 | 1 | 19.24 | 19 | 12 - 26 | 15 |
| ~ Speed | 2.68 | 3 | 0 - 6 | 1 | 20.18 | 20 | 13 - 28 | 16 | ||
| None | 5.10 | 5 | 2 - 9 | 3 | 42.94 | 43 | 33 - 54 | 37 | ||
| Mortality | 0.55 | 2.03 | 2 | 0 - 4 | 1 | 16.78 | 17 | 10 - 24 | 13 | |
| ~ Speed | 2.44 | 2 | 0 - 5 | 1 | 18.02 | 18 | 12 - 25 | 14 | ||
| None | 4.54 | 4 | 1 - 8 | 3 | 37.48 | 37 | 28 - 48 | 32 |
Figure S31. Posterior distributions of collision and mortality estimates for fin whales (a - b) and humpback whales (c-d), for each traffic scheme we analyzed.
Figure S32. Share of collision and mortality risk attributable to each vessel type, in 2019 and in 2030.
| Waterway | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 |
|---|---|---|---|---|---|---|---|---|
| Caamano | 59 | 29 | 61 | 30 | 17 | 9 | 17 | 10 |
| Estevan | 0 | 0 | 0 | 0 | 5 | 8 | 4 | 8 |
| Campania | 25 | 11 | 23 | 13 | 7 | 4 | 7 | 4 |
| Squally | 15 | 59 | 15 | 56 | 5 | 16 | 5 | 16 |
| Whale | 0 | 1 | 1 | 1 | 39 | 50 | 39 | 50 |
| Wright | 0 | 0 | 0 | 0 | 14 | 7 | 15 | 7 |
| McKay | 0 | 0 | 0 | 0 | 12 | 5 | 12 | 5 |
| Verney | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 |
Figure S33. Share of collision and mortality risk attributable to each waterway, in 2019 and in 2030.
| Month | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 |
|---|---|---|---|---|---|---|---|---|
| 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 1 |
| 5 | 4 | 5 | 5 | 5 | 3 | 3 | 3 | 3 |
| 6 | 21 | 18 | 23 | 18 | 17 | 16 | 17 | 17 |
| 7 | 19 | 21 | 16 | 19 | 11 | 11 | 11 | 11 |
| 8 | 30 | 27 | 27 | 29 | 30 | 36 | 30 | 35 |
| 9 | 21 | 19 | 23 | 21 | 32 | 27 | 32 | 27 |
| 10 | 3 | 7 | 3 | 7 | 5 | 5 | 5 | 5 |
| 11 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
Figure S34. Share of collision and mortality risk attributable to each month, in 2019 and in 2030.
| Diel period | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 | 2019 | 2030 |
|---|---|---|---|---|---|---|---|---|
| day | 80 | 73 | 83 | 72 | 61 | 61 | 60 | 62 |
| night | 20 | 27 | 17 | 28 | 39 | 39 | 40 | 38 |
Figure S35. Share of collision and mortality risk attributable to each diel period, in 2019 and in 2030.
| Species | Chances (%) of… | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Fin whale | Zero | 33.1 | 37.7 | 14.0 | 19.1 | 28.5 | 33.7 | 83.4 | 85.6 | 3.8 | 6.0 |
| At least 1 | 66.9 | 62.3 | 86.0 | 80.9 | 71.5 | 66.3 | 16.6 | 14.4 | 96.2 | 94.0 | |
| At least 2 | 32.9 | 26.6 | 55.0 | 45.8 | 34.8 | 27.1 | 1.3 | 0.9 | 83.7 | 76.0 | |
| At least 3 | 11.1 | 7.5 | 27.1 | 20.9 | 13.8 | 9.3 | 0.0 | 0.0 | 65.2 | 52.8 | |
| At least 4 | 3.4 | 1.6 | 11.7 | 8.5 | 4.8 | 2.1 | 0.0 | 0.0 | 41.9 | 30.9 | |
| At least 5 | 0.6 | 0.2 | 5.2 | 2.6 | 0.9 | 0.4 | 0.0 | 0.0 | 24.2 | 16.5 | |
| Humpback whale | Zero | 0.0 | 0.3 | 0.0 | 0.0 | 0.0 | 0.0 | 18.7 | 25.4 | 0.0 | 0.0 |
| At least 1 | 100.0 | 99.7 | 100.0 | 100.0 | 100.0 | 100.0 | 81.3 | 74.6 | 100.0 | 100.0 | |
| At least 2 | 99.8 | 99.4 | 100.0 | 100.0 | 100.0 | 100.0 | 49.4 | 38.3 | 100.0 | 100.0 | |
| At least 3 | 99.1 | 97.9 | 100.0 | 100.0 | 100.0 | 99.8 | 24.3 | 18.1 | 100.0 | 100.0 | |
| At least 4 | 97.8 | 96.1 | 100.0 | 99.8 | 99.9 | 99.6 | 9.7 | 6.2 | 100.0 | 100.0 | |
| At least 5 | 95.6 | 89.8 | 99.9 | 99.4 | 99.5 | 98.6 | 3.0 | 1.3 | 100.0 | 100.0 |
| Species | Chances (%) of… | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. | Coll. | Mort. |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Fin whale | Zero | 33.1 | 37.7 | 14.0 | 19.1 | 83.4 | 85.6 | 28.5 | 33.7 | 3.8 | 6.0 |
| Max of 1 | 67.1 | 73.4 | 45.0 | 54.2 | 98.7 | 99.1 | 65.2 | 72.9 | 16.3 | 24.0 | |
| Max of 2 | 88.9 | 92.5 | 72.9 | 79.1 | 100.0 | 100.0 | 86.2 | 90.7 | 34.8 | 47.2 | |
| Max of 3 | 96.6 | 98.4 | 88.3 | 91.5 | 100.0 | 100.0 | 95.2 | 97.9 | 58.1 | 69.1 | |
| Max of 4 | 99.4 | 99.8 | 94.8 | 97.4 | 100.0 | 100.0 | 99.1 | 99.6 | 75.8 | 83.5 | |
| Max of 5 | 99.7 | 99.8 | 98.3 | 99.3 | 100.0 | 100.0 | 99.6 | 99.8 | 87.6 | 93.1 | |
| Humpback whale | Zero | 0.0 | 0.3 | 0.0 | 0.0 | 18.7 | 25.4 | 0.0 | 0.0 | 0.0 | 0.0 |
| Max of 1 | 0.2 | 0.6 | 0.0 | 0.0 | 50.6 | 61.7 | 0.0 | 0.0 | 0.0 | 0.0 | |
| Max of 2 | 0.9 | 2.1 | 0.0 | 0.0 | 75.7 | 81.9 | 0.0 | 0.2 | 0.0 | 0.0 | |
| Max of 3 | 2.2 | 3.9 | 0.0 | 0.2 | 90.3 | 93.8 | 0.1 | 0.4 | 0.0 | 0.0 | |
| Max of 4 | 4.4 | 10.2 | 0.1 | 0.6 | 97.0 | 98.7 | 0.5 | 1.4 | 0.0 | 0.0 | |
| Max of 5 | 9.9 | 20.7 | 0.5 | 1.7 | 99.2 | 99.8 | 1.2 | 4.3 | 0.0 | 0.0 |
## Melting outcomes & prepping the posterior ...
## Determining the probability of your observations ...
## Likelihood of your observation, assuming perfect detection = 0.003
## Finding the strike detection rate (SDR) that would make your observations plausible ...
## preparing L ~ SDR plot ...
## --- SDR needed for P(Observation) of 0.05 = 0.455
## --- SDR needed for P(Observation) of 0.10 = 0.355
## --- SDR needed for P(Observation) of 0.20 = 0.235
## --- SDR needed for P(Observation) of 0.55 = 0.095
Figure S36. Results of ship-strike model validation for fin whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.
## Melting outcomes & prepping the posterior ...
## Determining the probability of your observations ...
## Likelihood of your observation, assuming perfect detection = 0
## Finding the strike detection rate (SDR) that would make your observations plausible ...
## preparing L ~ SDR plot ...
## --- SDR needed for P(Observation) of 0.05 = 0.16
## --- SDR needed for P(Observation) of 0.10 = 0.13
## --- SDR needed for P(Observation) of 0.20 = 0.085
## --- SDR needed for P(Observation) of 0.55 = 0.03
Fig S37. Results of ship-strike model validation for humpback whales, in which the likelihood of not observing a strike in the last decade was estimated according to our model results. Left: Distribution of strike observations predicted with our models when assuming perfect detection (i.e., no strikes missed). The red dashed line indicates what we actually observed. Right: The probability of our observations under various scenarios of imperfect detection. Dashed lines indicate conventional alpha levels of significance.
Figure S38. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for fin whales, when those measures are applied to different months of the year for various durations (one - three months).
Figure S39. Efficacy of mitigation categories 3 (LNG rescheduling) and 4 (LNG moratoria) for humpback whales, when those measures are applied to different months of the year for various durations (one - three months).
# Fin whales (Gitga'at average)
0.014 / 0.007 # eez (Wright)
## [1] 2
0.014 / 0.002 # north coast (Wright)
## [1] 7
0.014 / 0.003 # vancouver island (Nichol)
## [1] 4.666667
# Fin whales (Squally Ch)
0.031 / 0.007 # eez
## [1] 4.428571
0.031 / 0.002 # north coast
## [1] 15.5
0.031 / 0.003
## [1] 10.33333
# Humpback whales (Gitga'at average)
0.079 / 0.016 # eez (Wright)
## [1] 4.9375
0.079 / 0.025 # north coast (Wright)
## [1] 3.16
0.079 / 0.014 # vancouver island (Nichol)
## [1] 5.642857
# Humpback whales (Wright Sound)
0.0117 / 0.016 # eez
## [1] 0.73125
0.0117 / 0.025 # north coast
## [1] 0.468
0.0117 / 0.014
## [1] 0.8357143